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Visible and near-infrared (Vis–NIR) spectroscopy can provide a rapid and inexpensive estimation for soil organic carbon (SOC). However, with respect to field in situ spectroscopy, external environmental factors likely degrade the model accuracy. Among these factors, moisture has the greatest effect on soil spectra. The external parameter orthogonalization (EPO) algorithm in combination with the Chinese soil spectroscopic database (Dataset A, 1566 samples) was investigated to eliminate the interference of the external parameters for SOC estimation. Two different methods of EPO development, namely, laboratory-rewetting archive soil samples and field-collecting actual moist samples, were compared to balance model performance and analytical cost. Memory-based learning (MBL), a local modeling technique, was introduced to compare with partial least square (PLS), a global modeling method. A total of 250 soil samples from Central China were collected. Of these samples, 120 dry ground samples (Dataset B) were rewetted to different moisture levels to develop EPO P1 matrix. Seventy samples (Dataset C) containing field-moist intact and laboratory dry ground soils were used to establish EPO P2 matrix. The remaining 60 samples (Dataset D) also containing field-moist intact and laboratory dry ground soils were employed to validate the spectral models developed based on Dataset A. Results showed that EPO could correct the effect of external factors on soil spectra. For PLS, the validation statistics were as follows: no correction, validation R2 = 0.02; P1 correction, validation R2 = 0.56; and P2 correction, validation R2 = 0.57. For MBL, the validation results were as follows: no correction, validation R2 = 0.06; P1 correction, validation R2 = 0.65; and P2 correction, validation R2 = 0.69. The P2 consistently yielded better results than P1 did but simultaneously increased the sampling time and economic cost. The use of the P1 matrix and the MBL algorithm was recommended because it could reduce the cost of establishing in situ models for SOC. [ABSTRACT FROM AUTHOR]

The source identification and apportionment of heavy metals (HMs) is a vital issue for restoring contaminated soil. In this study, qualitative approaches [a finite mixture distribution model (FMDM) and raster-based principal components analysis (RB-PCA)] and a quantitative approach [positive matrix factorization (PMF)] were composed to identify and apportion the sources of five HMs (Cd, Hg, As, Pb, Cr) in Wenzhou City, China, using several crucial auxiliary variables. An initial ecological risk assessment suggested that the ecological risk level in the study area was generally considered low, with the greatest contamination contributions coming from Cd and Hg. The result of the FMDM showed that Cd and Pb fit a single log-normal distribution, Hg fit a double log-normal mixed distribution, and As and Cr presented a triple log-normal distribution. Each element was identified and separated from its natural or anthropogenic sources. A map of RB-PCA combined with an analysis of corresponding auxiliary variables suggested that the three main contribution sources in the entire study area were parental materials, industrial and agricultural mixed pollution, and mining exploration activities. Each element was discussed, using the PMF model, with regard to its quantitative contributions. Parental materials contributed to all elements (Cd, Hg, As, Pb, Cr) at 89.22%, 7.31%, 35.84%, 84.81% and 27.42%, respectively. Industrial emissions and agricultural inputs mixed pollution contributed 2.94%, 80.77%, 15.93%, 4.79%, and 25.63%, respectively. Mining activities contributed 7.84%,11.92%, 48.23%, 10.40% and 46.95%, respectively, to the five HMs. Such result could be used efficiently to generate scientific decisions and strategies in terms of decision-making on regulating HM pollution in soils. [ABSTRACT FROM AUTHOR]

• Obtained the highest resolution 3D velocity model for the XLD Reservoir so far. • Inverse velocity model uses both machine-learning data and phases of dense stations. • The seismicity in the head area and around the Manao Fault is influenced by fluids. • Two M4 events occurred on the east of the Lianfeng Fault are tectonic activity. The Xiluodu Reservoir (XLD), the third hydropower station developed downstream of the Jinsha River, is currently the fourth largest hydropower station worldwide. The reservoir has been impounded for 10 years, and numerous earthquakes have occurred, thus indicating an increased seismic risk. In existing studies, the deep tectonics and fine-scale structure in the reservoir area have not been sufficiently explained. Thus, the mechanism underlying reservoir-induced seismicity in this area remains unclear. In this study, we utilized a microseismic catalogue compiled based on the LOC-FLOW workflow (Li et al., 2023), alongside long-term observation data from a dense seismic array in the Jinsha River downstream, to obtain high-precision 3D V P , V S and V P /V S structures, as well as refined seismic relocations in the XLD Reservoir area. Additionally, we incorporated petrological, geomagnetic, gravity, crustal density, geodetic observation and numerical simulation data, which demonstrate that seismicity in the reservoir head area and near the Manao Fault is influenced by fluids. Moreover, the two M4 earthquakes that occurred east of the Lianfeng Fault are indicative of tectonic activity. Of these earthquakes, the Tianba earthquake cluster in the reservoir head area is located in a high-V P /V S zone, while a low-V S anomaly channel is observed here, which suggests that large amounts of fluid infiltrated along the fault, increasing the pore pressure and reducing the effective stress on the fault. The Wuji earthquake cluster in the head area is also located in a low-V P /V S zone, which indicates a low porosity and possibly undrained conditions. Thus, the earthquakes in this area are the result of coupled elastic stress-pore water pressure interactions. [ABSTRACT FROM AUTHOR]

In this study, we report a first major effort to measure surface wave amplitudes and to map attenuation structures of the Chinese mainland with dense modern broadband seismic networks in the country. We developed a method of phase‐matched filtering to automatically extract fundamental‐mode Rayleigh waves and to measure the spectral amplitudes. The results are compatible with those from the previous manual method with great improvement in efficiency. Using the automatic method, we extracted a large quantity of the amplitudes of Rayleigh waves at periods of 10 and 20 s recorded by 141 broadband stations from the China Digital Seismograph Network and 656 broadband stations from the China Regional Seismic Network. We performed tomographic inversions using the method of two‐station amplitude ratios and obtained images of the surface wave attenuation maps at periods of 10 and 20 s for the Chinese mainland. The tomographic model resolution reaches 1–2° in central and eastern China, 3–5° in western China, and 5° in the southeastern margin of the Tibetan Plateau and northeastern China. The tomographic results demonstrate good correspondence with geological structures. The distribution of strong historical earthquakes indicates that in the Chinese mainland, these earthquakes occurred mainly in high‐attenuation areas or the junctions between high‐ and low‐attenuation areas. Key Points: A first major effort was made to map surface wave attenuation structures of the Chinese mainland using dense networks of stationsAn automatic method was developed to extract the fundamental‐mode Rayleigh waves with great improvement of efficiencyThe attenuation maps show important geological structures, correlation with seismicity, and similarity and contrast with seismic velocity [ABSTRACT FROM AUTHOR]

It is a great challenge to identify the many and varied sources of soil heavy metal pollution. Often little information is available regarding the anthropogenic factors and enterprises that could potentially pollute soils. In this study we use freely available geographical data from a search engine in conjunction with machine learning methodologies to identify and classify potentially polluting enterprises in the Yangtze Delta, China. The data were classified into 31 separate and four integrated industry types by five different machine learning approaches. Multinomial naive Bayesian (NB) methods achieved an accuracy of 87% and Kappa coefficient of 0.82 and were used to classify the geographic data from more than 260,000 enterprises. The relationship between the different industry classes and measurements of soil cadmium (Cd) and mercury (Hg) concentrations was explored using bivariate local Moran's I analysis. The analysis revealed areas where different industry classes had led to soil pollution. In the case of Cd, elevated concentrations also occurred in some areas because of excessive fertilization and coal mining. This study provides a new approach to investigate the interaction between anthropogenic pollution and natural sources of soil heavy metals to inform pollution control and planning decisions regarding the location of industrial sites. Image 1 • Potentially polluting enterprises are identified and classified. • Spatial correlation of Cd and Hg with polluting enterprises is observed. • Industry pollution affects the distribution of Cd and Hg pollution in soils. • High contents of Cd occur in some areas due to fertilization and coal mining. • Hg pollution caused by chemical industry is more serious than other industries. Capsule: This work provides a new way based on machine learning methods using geographic dataset for pollution source identification and risk mitigation. [ABSTRACT FROM AUTHOR]

In this study we systematically reviewed 1203 research papers published between 2008 and 2018 in China and recorded related data on eight kinds of soil heavy metals (Cr, Pb, Cd, Hg, As, Cu, Zn, and Ni). Based on that, the pollution levels, ecological risk and health risk caused by soil heavy metals were evaluated and the pollution hot spots and potential driving factors of different heavy metals in different provinces were also identified. Results indicated accumulation of heavy metals in soils of most provinces in China compared with background values. Consistent with previous findings, the most prevalent polluted heavy metals were Cd and Hg. Polluted regions are mainly located in central, southern and southwestern China. Hunan, Guangxi, Yunnan, and Guangdong provinces were the most polluted provinces. For the potential health risk caused by heavy metals pollution, children are more likely confront with non-carcinogenic risk than adults and seniors. And children in Hunan and Guangxi province were experiencing relatively larger non-carcinogenic risk. In addition, children in part of provinces were undergoing potentially carcinogenic risks due to soil heavy metals exposure. Furthermore, in our study the 31 provinces in mainland China were divided into six subsets according to corresponding potential driving factors for heavy metal accumulation. Our study provide more comprehensive and updated information for contributing to better soil management, soil remediation, and soil contamination control in China. Image 1 • Cd and Hg were the most polluted heavy metals in soil across China. • The ER values for Cd in 30 provinces varied from moderate to very high risk. • Hunan, Guangxi, Yunnan and Guangdong were confirmed as priority control provinces. • Children are undergo larger health risk than adults and seniors in China. • Controlling factors of heavy metals accumulation in different provinces were mapped. [ABSTRACT FROM AUTHOR]

The spatio-temporal variation and temporal changes in the sources of Cr, Pb, Cd, Hg, and As in soil on the Hangzhou–Jiaxing–Huzhou (H-J-H) Plain were analysed based on 4,359 soil samples collected in 2002 and 2012. Geostatistical and spatial analysis methods were used to explore the spatio-temporal variation in the pollution levels and 'pollution hotspots' for potentially toxic elements (PTEs), and the positive matrix factor model was used to quantitatively appoint and analyse temporal changes in PTE sources. The results indicated that the PTE content in most parts of the survey area were at a safe level in both 2002 and 2012, but a clearly upward trend was detected for Cr, Pb, and Cd. Moreover the pollution index for Cr, Pb, Cd, and the Nemerow composite pollution index increased in the west but decreased in the east of the H-J-H Plain from 2002 to 2012. The pollution index for Hg and As presented the opposite spatial pattern. It is obvious that there have been changes in the spatial pattern of pollution hotspots for PTEs on the H-J-H Plain from 2002 to 2012. Four sources of PTEs in soil were quantitatively appointed. In 2002, 2012, the dominant sources of Cr, Cd, Hg, and As were soil parent materials, industrial activities, atmospheric deposition and agricultural inputs, respectively. The dominant source of Pb in the soil changed from traffic emissions to soil parent materials, indicating the benefit of banning the use of leaded gasoline in China. This study highlights the importance of monitoring soil environmental quality and highlights the significance of spatio-temporal variation in PTEs in suburban zones or transitional areas undergoing rapid industrialization and urbanization, like the H-J-H Plain. Image 1 • An upward trend for content of Cr, Pb and Cd in soil was detected from 2002 to 2012. • An increasing trend for pollution index of Pb and Cd was found during 2002 and 2012. • The spatial pattern of toxic elements pollution hotspots was obviously changed. • Dominant source of Pb was changed from traffic emissions to soil parent materials. • No change occurred for the source of Cr, Cd, Hg and As in soil from 2002 to 2012. [ABSTRACT FROM AUTHOR]

Potentially toxic elements (PTEs) pollution in the agricultural soil of China, especially in developed regions such as the Yangtze River Delta (YRD) in eastern China, has received increasing attention. However, there are few studies on the long-term assessment of soil pollution by PTEs over large regions. Therefore, in this study, a meta-analysis was conducted to evaluate the current state and temporal trend of PTEs pollution in the agricultural land of the Yangtze River Delta. Based on a review of 118 studies published between 1993 and 2020, the average concentrations of Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni were found to be 0.25 mg kg -1 , 0.14 mg kg -1 , 8.14 mg kg -1 , 32.32 mg kg -1 , 68.84 mg kg -1 , 32.58 mg kg -1 , 92.35 mg kg -1 , and 29.30 mg kg -1 , respectively. Among these elements, only Cd and Hg showed significant accumulation compared with their background values. The eastern Yangtze River Delta showed a relatively high ecological risk due to intensive industrial activities. The contents of Cd, Pb, and Zn in soil showed an increasing trend from 1993 to 2000 and then showed a decreasing trend. The results obtained from this study will provide guidance for the prevention and control of soil pollution in the Yangtze River Delta.

Purpose: This study aimed to examine the psychometric properties and performance of a Chinese version of the Female Sexual Function Index (FSFI) among a sample of Chinese women with cervical cancer., Methods: A cross-sectional survey design was used. The respondents included 215 women with cervical cancer in an oncology hospital in China. A translated Chinese version of the FSFI was used to investigate their sexual functioning. Psychometric testing included internal consistency reliability (Cronbach's alpha coefficient and item-total correlations), test-retest reliability, construct validity (principal component analysis via oblique rotation and confirmatory factor analysis), and variability (floor and ceiling effects)., Results: The mean score of the total scale was 20.65 ± 4.77. The Cronbach values were .94 for the total scale, .72-.90 for the domains. Test-retest correlation coefficients over 2-4 weeks were .84 (p < .05) for the total scale, .68-.83 for the subscales. Item-total correlation coefficients ranged between .47 and .83 (p < .05). A five-factor model was identified via principal component analysis and established by confirmatory factor analysis, including desire/arousal, lubrication, orgasm, satisfaction, and pain. There was no evidence of floor or ceiling effects., Conclusions: With good psychometric properties similar to its original English version, this Chinese version of the FSFI is demonstrated to be a reliable and valid instrument that can be used to assess sexual functioning of women with cervical cancer in China. Future research is still needed to confirm its psychometric properties and performance among a large sample., (Copyright © 2015 Elsevier Ltd. All rights reserved.)